Multiomics characterization and verification of clear cell renal cell carcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Abstract

Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor with different genetic and molecular alterations. Schemes for ccRCC classification system based on multiomics are urgent, to promote further biological insights. Two hundred and fifty‐five ccRCC patients with paired data of clinical information, transcriptome expression profiles, copy number alterations, DNA methylation, and somatic mutations were collected for identification. Bioinformatic analyses were performed based on our team's recently developed R package “MOVICS.” With 10 state‐of‐the‐art algorithms, we identified the multiomics subtypes (MoSs) for ccRCC patients. MoS1 is an immune exhausted subtype, presented the poorest prognosis, and might be caused by an exhausted immune microenvironment, activated hypoxia features, but can benefit from PI3K/AKT inhibitors. MoS2 is an immune “cold” subtype, which represented more mutation of VHL and PBRM1, favorable prognosis, and is more suitable for sunitinib therapy. MoS3 is the immune “hot” subtype, and can benefit from the anti‐PD‐1 immunotherapy. We successfully verified the different molecular features of the three MoSs in external cohorts GSE22541, GSE40435, and GSE53573. Patients that received Nivolumab therapy helped us to confirm that MoS3 is suitable for anti‐PD‐1 therapy. E‐MTAB‐3267 cohort also supported the fact that MoS2 patients can respond more to sunitinib treatment. We also confirm that SETD2 is a tumor suppressor in ccRCC, along with the decreased SETD2 protein level in advanced tumor stage, and knock‐down of SETD2 leads to the promotion of cell proliferation, migration, and invasion. In summary, we provide novel insights into ccRCC molecular subtypes based on robust clustering algorithms via multiomics data, and encourage future precise treatment of ccRCC patients.

Integrated single-cell and bulk characterization of branched chain amino acid metabolism-related key gene BCAT1 and association with prognosis and immunogenicity of clear cell renal cell carcinoma

“…In the high-BMS group exhibited higher TME scores and increased immunosuppressive cell infiltration, correlating with a worse prognosis. This observation aligns with the immune exhaustion phenotype reported in Meng et al’s study [ 32 ]. While immune checkpoint blocking therapy and targeted therapy are indispensable in the management of ccRCC [ 33 ], formulating an optimal personalized treatment plan remains a challenge for clinicians.…”

Clinical features and molecular landscape of cuproptosis signature‐related molecular subtype in gastric cancer

“…An increasing number of studies have shown that the cellular cuproptosis mechanism plays a great role in tumor development and progression [ 35 ]. The utilization of multi‐omics technology has enabled the identification of cancer biomarkers generated by tumor cells within the intricate tumor microenvironment, thereby significantly advancing the development of novel diagnostic and therapeutic approaches [ 36 ]. There have been studies constructing prognosis models based on copper death features, but they have not comprehensively considered clinical features, and the explanation of the genetic molecular landscape is not in‐depth enough [ 37 ].…”

LASSO regression and WGCNA-based telomerase-associated lncRNA signaling predicts clear cell renal cell carcinoma prognosis and immunotherapy response

“…Furthermore, our study is based on a genomics-level single survey. Meng et al [ 60 ] recently delineated the multi-body subtype (MoS) classification and proposed a multi-omics-based ccRCC classification system scheme, promoting further biological understanding of ccRCC. Finally, to confirm the mechanism of action of these model genes in ccRCC, additional in vitro investigations are necessary because of the limitations of our current in vitro studies.…”